• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.1
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• pp.47-54
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• 2012

Agriculture is dependable to weather condition and its change so that it is necessary to understand the impacts of climatic change. The aim of this study is to analyze the change of consumptive use of water and rice yield due to climate change using CERES-Rice. In this study, the weather data of three emission scenario of A1B, A2 and B1 created from CGCM (Coupled General Circulation Model) were used from 2011 to 2100, and downscaled daily weather data were simulated using LARS-WG (Long Ashton Research Station Weather Generator). The input data for cultivated condition for simulating CERSE (Crop-Environment Resource Synthesis)-Rice were created referring to standard cultivation method of paddy rice in Korea. The results showed that consumptive uses of water for paddy rice were projected decreasing to 4.8 % (2025s), 9.1 % (2055s), 12.6 % (2085s) comparing to the baseline value of 403.5 mm in A2 scenario. The rice yield of baseline was 450.7 kg/10a and projected increasing to -0.4 % (2025s), 3.9 % (2055s), 17.5 % (2085s) in A1B scenario. The results demonstrated relationships between consumptive use of water and rice yields due to climate change and can be used for the agricultural water resources development planning and cultivation method of paddy rice for the future.

• Ocean and Polar Research
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• v.26 no.2
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• pp.133-143
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• 2004

For the purpose of understanding the cloud scattering effect of UV radiation at King Sejong station In West Antarctica, we analyzed the data measured by UV-Biometer at surface and compared its result with solar radiation model. The parameterization of UV radiation by cloud ice crystal was applied to solar radiation model and the sensitivity of this model for the variation of ice crystal was tested. The cloud optical thickness was calculated by using this solar radiation model. It was compared the result from calculation with CERES satellite data. In solar radiation model, the UV radiation was less scattered with increase of ice crystal size in cloud and this scattering effect was more important to UV-A radiation than Erythemal UV-B radiation. But scattering effects by altitude of cloud was not serious. The calculated cloud optical thicknesses in Erythemal UV-B and UV-A region were compared with CERES satellite data and the result by UV-A was more accurate than Erythemal UV-B region.

• Journal of Environmental Science International
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• v.22 no.8
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• pp.1053-1062
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• 2013

The shortwave aerosol direct radiative forcing (SWARF) was analyzed using the Clouds and Earth's Radiant Energy System (CERES) data in the East Asian region from 2001 to 2010. In the Yellow Sea and the Korean Peninsula, located in the leeward side of China, significantly negative high SWARF at the top of atmosphere (TOA) occurs due to the long-range transport of anthropogenic (e.g. sulphate) and natural aerosols (e.g. mineral dust) from the East Asian continent. Conversely, eastern China has much higher levels of SWARF at the surface (SFC) due to anthropogenically emitted aerosol than in the Yellow Sea and the Korean Peninsula. Since the radiative forcing of aerosols in the atmosphere are different in type, aerosol types were classified into sea salt+sulphate, smoke, sulphate and dust by using satellite data. The analysis on the SWARF by the classified aerosol types indicated that sulphate occupies a predominant portion of the atmosphere in the Yellow Sea and the Korean Peninsula in the summer. In particular, the annual averages of the summer TOA SWARF increased in the Yellow Sea and the Korean Peninsula from 2001 to 2010.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.1
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• pp.37-43
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• 2001

Crop status monitoring and yield prediction at higher spatial resolution is a valuable tool in various decision making processes including agricultural policy making by the national and local governments. A prototype crop forecasting system was developed to project the size of rice crop across geographic areas nationwide, based on daily weather pattern. The system consists of crop models and the input data for 1,455 cultivation zone units (the smallest administrative unit of local government in South Korea called "Myun") making up the coterminous South Korea. CERES-rice, a rice crop growth simulation model, was tuned to have genetic characteristics pertinent to domestic cultivars. Daily maximum/minimum temperature, solar radiation, and precipitation surface on 1km by 1km grid spacing were prepared by a spatial interpolation of 63 point observations from the Korea Meteorological Administration network. Spatial mean weather data were derived for each Myun and transformed to the model input format. Soil characteristics and management information at each Myun were available from the Rural Development Administration. The system was applied to the forecasting of national rice production for the recent 3 years (1997 to 1999). The model was run with the past weather data as of September 15 each year, which is about a month earlier than the actual harvest date. Simulated yields of 1,455 Myuns were grouped into 162 counties by acreage-weighted summation to enable the validation, since the official production statistics from the Ministry of Agriculture and Forestry is on the county basis. Forecast yields were less sensitive to the changes in annual climate than the reported yields and there was a relatively weak correlation between the forecast and the reported yields. However, the projected size of rice crop at each county, which was obtained by multiplication of the mean yield with the acreage, was close to the reported production with the $r^2$ values higher than 0.97 in all three years.

• Korean Journal of Remote Sensing
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• v.20 no.3
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• pp.175-188
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• 2004

The objectives of this study were to estimate leaf area index (LAI) as a function of image-derived vegetation indices, and to compare measured and estimated LAI to the results of crop model simulation. Soil moisture, crop phenology, and LAI data were obtained several times during the 2001 growing season at monitoring sites established in two central Missouri experimental fields, one planted to com (Zea mays L.) and the other planted to soybean (Glycine max L.). Hyper- and multi-spectral images at varying spatial. and spectral resolutions were acquired from both airborne and satellite platforms, and data were extracted to calculate standard vegetative indices (normalized difference vegetative index, NDVI; ratio vegetative index, RVI; and soil-adjusted vegetative index, SAVI). When comparing these three indices, regressions for measured LAI were of similar quality $(r^2$ =0.59 to 0.61 for com; $r^2$ =0.66 to 0.68 for soybean) in this single-year dataset. CERES(Crop Environment Resource Synthesis)-Maize and CROPGRO-Soybean models were calibrated to measured soil moisture and yield data and used to simulate LAI over the growing season. The CERES-Maize model over-predicted LAI at all corn monitoring sites. Simulated LAI from CROPGRO-Soybean was similar to observed and image-estimated LA! for most soybean monitoring sites. These results suggest crop growth model predictions might be improved by incorporating image-estimated LAI. Greater improvements might be expected with com than with soybean.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.4
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• pp.229-241
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• 2006

Global air temperature has risen by $0.6^{\circ}C$ over the last one hundred years due to increased atmospheric greenhouse gases. Moreover, this global warming trend is projected to continue in the future. This study was carried out to evaluate spatial variations in rice production areas by simulating rice-growth and development with projected high resolution climate data in Korea far 2011-2100, which was geospatially interpolated from the 25 km gridded data based on the IPCC SRES A2 emission scenario. Satellite remote sensing data were used to pinpoint the rice-growing areas, and corresponding climate data were aggregated to represent the official 'crop reporting county'. For the simulation experiment, we used a CERES-Rice model modified by introducing two equations to calculate the leaf appearance rate based on the effective temperature and existing leaf number and the final number of leaves based on day-length in the photoperiod sensitive phase of rice. We tested the performance of this model using data-sets obtained from transplanting dates and nitrogen fertilization rates experiments over three years (2002 to 2004). The simulation results showed a good performance of this model in heading date prediction [$R^2$=0.9586 for early (Odaebyeo), $R^2$=0.9681 for medium (Hwasungbyeo), and $R^2$=0.9477 for late (Dongjinbyeo) maturity cultivars]. A modified version of CERES-Rice was used to simulate the growth and development of three Japonica varieties, representing early, medium, and late maturity classes, to project crop status for climatological normal years between 2011 and 2100. In order to compare the temporal changes, three sets of data representing 3 climatological years (2011-2040, 2041-2070, and 2071-2100) were successively used to run the model. Simulated growth and yield data of the three Japonica cultivars under the observed climate for 1971-2000 was set as a reference. Compared with the current normal, heading date was accelerated by 7 days for 2011-2040 and 20 days for 2071-2100. Physiological maturity was accelerated by 15 days for 2011-2040 and 30 days for 2071-2100. Rice yield was in general reduced by 6-25%, 3-26%, and 3-25% per 10a in early, medium, and late maturity classes, respectively. However, mid to late maturing varieties showed an increased yield in northern Gyeonggi Province and in most of Kwangwon Province in 2071-2100.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.4
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• pp.192-203
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• 2011

The CERES-Barley crop simulation model was used to assess the impacts of climate change on the potential yield of winter naked barley in Korea. Fifty six sites over the southern part of the Korean Peninsula were selected to compare the climate change impacts in various climatic conditions. Based on the A1B climate change scenarios of Korea, the present climatological normal (1971-2000) and the three future ones (2011-2040, 2041-2070, and 2071-2100) were considered in this study. The three future normals were divided by three environmental conditions with changes in: (1) temperature only, (2) carbon dioxide concentration only, and (3) both temperature and carbon dioxide concentration. The agreement between the observed and simulated outcomes was reasonable with the coefficient of determination of grain yield to be 0.78. We concluded that the CERES-Barley model was suitable for predicting climate change impacts on the potential yield of winter naked barley. The effect of the increased temperature only with the climate change scenario was negative to the potential yield of winter naked barley, which ranges from -34 to -9% for the three future normals. However, the effect of the elevated carbon dioxide concentration only on the potential yield of winter naked barley was positive, ranging from 6 to 31% for the three future normals. For the elevated conditions of both temperature and carbon dioxide concentration, the potential yields increased by 8, 15, and 13% for the 2011-2040, 2041-2070, and 2071-2100 normals, respectively.

• Journal of Climate Change Research
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• v.2 no.4
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• pp.317-331
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• 2011

The CERES-Barley crop simulation model of DSSAT package was used to assess the impacts of climate change on potential yield of winter covered barley in Korea. 56 sites over the southern part of Korean peninsula were selected to compare the climate change impacts in various climatic conditions. The climatological normals (1971~2000) and the three future climatological normals (2011~2040, 2041~2070, and 2071~2100), based on A1B climate change scenarios of Korea, were used in this study, and the three future climatological normals were simulated under three environmental conditions, where only temperature change, only carbon dioxide change, and both of temperature and carbon dioxide change with future A1B climate change scenarios, respectively. Results: The CERES-Barley model was suitable for predicting climate change impacts on the potential yield of winter covered barley, because of the agreement between observed and simulated outcomes (e.g., the coefficient of determination of grain yield equals 0.84). (1) The only increased temperature effect with the climate change scenarios was mostly negative to the potential yield of winter covered barley and its magnitude ranges from -21% to +1% for the three future normals. (2) The effect of the only elevated carbon dioxide on the potential yield of winter covered barley was positive and its magnitude ranged from 12% to 43% for the three future normals. (3) For increased temperature and elevated carbon dioxide change cases, potential yields increased by 13%, 21%, 19% increase for the 2011~2040, 2041~2070, 2071~2100 normals, respectively.

• Journal of Astronomy and Space Sciences
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• v.40 no.2
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• pp.67-77
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• 2023

The Titius-Bode's relation has been historically successful in predicting the location of Ceres in the solar system, while its physical basis remains hidden. In this study, we attempt to answer the question of whether the Titius-Bode's relation is universally valid for exoplanetary systems with plural exoplanets. For this purpose, we statistically study the distribution of the ratio of the orbiting periods of two planets in 32 exoplanetary systems hosted by a single star. We only consider the period ratios derived from exoplanets orbiting a single star since celestial objects under investigation are kept as simple as possible and free from uncertainties such as the mass of the host star. We find that the distribution of period ratios of two exoplanets appears inconsistent with that derived from the Titius-Bode's relation using the χ² test. We also found that the distance distribution in exoplanetary systems unlikely follows the uniform distribution or the Poisson's distribution. It is noted, however, that more rigorous statistical tests should be carried out to reach a more certain conclusion.

• Korean Journal of Agricultural and Forest Meteorology
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• v.4 no.4
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• pp.224-236
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• 2002

A long-term growth simulation was performed at 496 land units in the western coastal plains (WCP) of North Korea to test the potential adaptability of each land unit for growing South Korean rice cultivars. The land units for rice cultivation (CZU), each of them represented by a geographically referenced 5 by 5 km grid tell, were identified by analyzing satellite remote sensing data. Surfaces of monthly climatic normals for daily maximum and minimum temperature, precipitation number of rain days and solar radiation were generated at a 1 by 1 km interval by spatial statistical methods using observed data at 51 synoptic weather stations in North and South Korea during 1981-2000. Grid cells felling within a same CZU and, at the same time, corresponding to the satellite data- identified rice growing pixels were extracted and aggregated to make a spatially explicit climatic normals relevant to the rice growing area of the CZU. Daily weather dataset for 30 years was randomly generated from the monthly climatic normals of each CZU. Growth and development parameters of CERES-rice model suitable for 11 major South Korean cultivars were derived from long-term field observations. Eight treatments comprised of 2 transplanting dates $\times$ 2 cropping systems $\times$ 2 irrigation methods were assigned to each cultivar. Each treatment was simulated with the randomly generated 30 years' daily weather data (from planting to physiological maturity) for 496 land units in WCP to simulate the growth and yield responses to the interannual climate variation. The same model was run with the input data from the 3 major crop experiment stations in South Korea to obtain a 30 year normal performance of each cultivar, which was used as a "reference" for comparison. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to evaluate the suitability of each land unit for growing a specific South Korean cultivar. The results may be utilized as decision aids for agrotechnology transfer to North Korea, for example, germplasm evaluation, resource allocation and crop calendar preparation.